Ricerc@Sapienza

Inventory optimization of high-value spare parts may generate a significant reduction of cost to allow a better allocation of resources in maintenance management. Sherbrooke’s METRIC (Multi Echelon Technique for Recoverable Item Control) is the most common method to define an overall optimization process adopting a system-approach. Its main assumption consists of adopting a Poisson distribution to describe the demand pattern of the items.

Nowadays, our society is increasingly becoming economically and socially dependent on the cyberspace. However, the cyberspace is exposed to numerous risks, and there is a constant threat of exploitable vulnerabilities, which could cause significant reputational and economic damages. For addressing these threats, the Italian National Cyber Security Framework was developed to offer an approach to assessing cyber risks into organizations, as well as to help improve the related security through focused investments. Still, this evaluation is not a straightforward endeavour.

The rapid development and adoption of Internet and digital technologies
dramatically changed business processes, leading to a disruptive digital transformation
of the whole industry value chain. The so-called Industry 4.0 refers to a
complex evolution of the entire industrial sector that includes technological
advances in production equipment (i.e. Additive Manufacturing), smart finished
products (IoT), data tools and analytics, involving activities and stakeholders at all

Models of human habits in smart spaces can be expressed by using a multitude of representations whose readability influences the possibility of being validated by human experts. Our research is focused on developing a visual analysis pipeline (service) that allows, starting from the sensor log of a smart space, to graphically visualize human habits. The basic assumption is to apply techniques borrowed from the area of business process automation and mining on a version of the sensor log preprocessed in order to translate raw sensor measurements into human actions.

In the era of Big Data and Internet-of-Things (IoT), all real-world environments are gradually becoming cyber-physical (e.g., emergency management, healthcare, smart manufacturing, etc.), with the presence of connected devices and embedded ICT systems (e.g., smartphones, sensors, actuators) producing huge amounts of data and events that influence the enactment of the Cyber Physical Processes (CPPs) enacted in such environments.

Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management.